Title: Wavelet transformation and cluster ensemble for gene expression analysis

Authors: Xiaohua Hu, Illhoi Yoo, Xiaodan Zhang, Payal Nanavati, Debjit Das

Addresses: College of Information Science and Technology, Drexel University, Philadelphia, PA 19104, USA. ' College of Information Science and Technology, Drexel University, Philadelphia, PA 19104, USA. ' College of Information Science and Technology, Drexel University, Philadelphia, PA 19104, USA. ' College of Information Science and Technology, Drexel University, Philadelphia, PA 19104, USA. ' College of Information Science and Technology, Drexel University, Philadelphia, PA 19104, USA

Abstract: This paper introduces a wavelet transformation and a cluster ensemble framework using graph theory for clustering gene expression data sets. The experiment results indicate that wavelet transformation and cluster ensemble approaches together yield better clustering results than the single best clustering algorithm on both synthetic and yeast gene expression data sets.

Keywords: wavelet transformation; cluster ensemble; yeast gene expression; clustering algorithms; graph theory; wavelets; bioinformatics; synthetic data sets.

DOI: 10.1504/IJBRA.2005.008447

International Journal of Bioinformatics Research and Applications, 2005 Vol.1 No.4, pp.447 - 460

Published online: 20 Dec 2005 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article